This research explores the idea that for certain optimization problems there is a way to parallelize the algorithm such that the parallel efficiency can exceed one hundred percent. Specifically, a parallel compiler, PC, is used to apply shortcutting techniquest to a metaheuristic Ant Colony Optimization (ACO), to solve the well-known Traveling Salesman Problem (TSP) on a cluster running Message Passing Interface (MPI). The results of both serial and parallel execution are compared using test datasets from the TSPLIB.
| Identifer | oai:union.ndltd.org:csusb.edu/oai:scholarworks.lib.csusb.edu:etd-project-4120 |
| Date | 01 January 2007 |
| Creators | D'Souza, Sammy Raymond |
| Publisher | CSUSB ScholarWorks |
| Source Sets | California State University San Bernardino |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses Digitization Project |
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